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Title: Net Electricity Clustering at Different Temporal Resolutions Using a SAX-Based Method for Integrated Distribution System Planning

Abstract

This paper addresses a major utility and regulator concern of characterizing customer net electricity consumption profiles to realize integrated distribution system planning. This is pivotal in assessing the capability of the power system to accommodate net load variability and its impacts on the grid such as voltage rise, narrowing peak demand duration, and reducing the cost of energy storage. Although the extant literature has focused on load clustering, this paper uses a symbolic aggregate approximation-based (SAX-based) dimensionality- reduction and k-means techniques to cluster net consumption of smart meter data for more than 3500 residential customers in a month at different temporal resolutions. This study proposes the use of cumulative explained variance in the principal component analysis to determine the optimal number of segments and dimensionality of the transformed space during discretization while retaining the data integrity instead of using intuition, as proposed by the extant literature. Also, this paper describes a screening methodology to determine the distribution of high-voltage customers among the resulting clusters of customers with and without on-site solar photovoltaic generation at different time resolutions.

Authors:
ORCiD logo [1];  [1]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S); Hawaiian Electric Company
OSTI Identifier:
1562868
Report Number(s):
NREL/JA-5D00-73858
Journal ID: ISSN 2169-3536
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
IEEE Access
Additional Journal Information:
Journal Volume: 7; Journal ID: ISSN 2169-3536
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; symbolic aggregate approximation; clustering; net electricity consumption; principal component analysis

Citation Formats

Emmanuel, Michael, and Giraldez, Julieta. Net Electricity Clustering at Different Temporal Resolutions Using a SAX-Based Method for Integrated Distribution System Planning. United States: N. p., 2019. Web. doi:10.1109/ACCESS.2019.2938212.
Emmanuel, Michael, & Giraldez, Julieta. Net Electricity Clustering at Different Temporal Resolutions Using a SAX-Based Method for Integrated Distribution System Planning. United States. doi:10.1109/ACCESS.2019.2938212.
Emmanuel, Michael, and Giraldez, Julieta. Thu . "Net Electricity Clustering at Different Temporal Resolutions Using a SAX-Based Method for Integrated Distribution System Planning". United States. doi:10.1109/ACCESS.2019.2938212. https://www.osti.gov/servlets/purl/1562868.
@article{osti_1562868,
title = {Net Electricity Clustering at Different Temporal Resolutions Using a SAX-Based Method for Integrated Distribution System Planning},
author = {Emmanuel, Michael and Giraldez, Julieta},
abstractNote = {This paper addresses a major utility and regulator concern of characterizing customer net electricity consumption profiles to realize integrated distribution system planning. This is pivotal in assessing the capability of the power system to accommodate net load variability and its impacts on the grid such as voltage rise, narrowing peak demand duration, and reducing the cost of energy storage. Although the extant literature has focused on load clustering, this paper uses a symbolic aggregate approximation-based (SAX-based) dimensionality- reduction and k-means techniques to cluster net consumption of smart meter data for more than 3500 residential customers in a month at different temporal resolutions. This study proposes the use of cumulative explained variance in the principal component analysis to determine the optimal number of segments and dimensionality of the transformed space during discretization while retaining the data integrity instead of using intuition, as proposed by the extant literature. Also, this paper describes a screening methodology to determine the distribution of high-voltage customers among the resulting clusters of customers with and without on-site solar photovoltaic generation at different time resolutions.},
doi = {10.1109/ACCESS.2019.2938212},
journal = {IEEE Access},
issn = {2169-3536},
number = ,
volume = 7,
place = {United States},
year = {2019},
month = {8}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Figures / Tables:

FIGURE 1 FIGURE 1: A typical behind-the-meter net consumption profile.

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